Acoustic Search and Detection of Oil Plumes Using an Autonomous Underwater Vehicle

Jimin Hwang,Neil Bose,Guy Williams,Hung Duc Nguyen

doi:10.3390/jmse8080618

Abstract

We introduce an adaptive sampling method that has been developed to support the Backseat Driver control architecture of the Memorial University of Newfoundland (MUN) Explorer autonomous underwater vehicle (AUV). The design is based on an acoustic detection and in-situ analysis program that allows an AUV to perform automatic detection and autonomous tracking of an oil plume. The method contains acoustic image acquisition, autonomous triggering, and thresholding in the search stage. A new biomimetic search pattern, the bumblebee flight path, was designed to maximize the spatial coverage in the oil plume detection phase. The effectiveness of the developed algorithm was validated through simulations using a two-dimensional planar plume model and a 90-degree scanning sensor model. The results demonstrate that the bumblebee search design combined with a genetic solution for the Traveling Salesperson Problem outperformed a conventional lawnmower survey, reducing the AUV travel distance by up to 75.3%. Our plume detection strategy, using acoustic sensing, provided data of plume location, distribution, and density, over a sector in contrast with traditional chemical oil sensors that only provide readings at a point.

Highlights

Oil spills can cause hazardous contamination of the ocean environment with potentially fatal consequences for marine wildlife
This could by utilizing response of thethe platform toor target parameters are unknown priorbetoachieved deployment, such as in-situ where data for real-time analysis withis an additional onboard computer a Backseat. In this the target is or where the target headed. This could be achieved bycalled utilizing in-situ data for real-time work, wewith developed a new onboard approachcomputer for an adaptive systemIn using a scanning sonar to analysis an additional called a sampling this work, we developed search for and detect a discontinuous and patchy plume resembling a real oil plume made up ofa a new approach for an adaptive sampling system using a scanning sonar to search for and detect droplets of oil.and
We have presented a new approach for an adaptive sampling system using a scanning sonar to search for and detect a discontinuous and patchy plume resembling a real oil plume made up of droplets of oil

Summary

Introduction

Oil spills can cause hazardous contamination of the ocean environment with potentially fatal consequences for marine wildlife. They may result in considerable socio-economic losses for coastal industries. The coalescent and clustering characteristics of oil often result in a discontinuous plume composed of countless undissolved droplets [2,3]. It is preferable that any detection methodology exerts as little influence on an oil plume as possible in the survey stage. This requires non-contact remote sensing adjacent to the plume, rather than active interaction within the plume, to take measurements

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